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THE TASK To examine whether age-related reduction in mPFC gray matter volume statistically mediate the effects of age on impaired NREM SWA and whether this age related interaction between brain atrophy and NREM SWA consequently predicts age-related failure of overnight episodic memory retention, and with it, the persistent reliance (rather than increasing independence) of memory retrieval on the hippocampus.

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General Experimental Design Participants entered the lab in the evening and trained to criterion on a sleep-dependant episodic memory task, followed by a short delay (10 min) recognition test. 8 hours sleep, measured with PSG at their habitual bed time. In 2 hours after waking participants performed an event-related fMRI scanning session while performing a long-delay (10 h) recognition test

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SWA predicts overnight memory change in young and older adults. Topographic plots of the association between relative SWA (0.8 - 4.6 Hz) during SWS and associative episodic memory change in all participants collapsed (a) and in young and older adults (b), with corresponding regression for young and older adults plotted for global relative SAW (c), defined as the average relative SWA across all electrode sites, and prefrontal SWA (d), defined as the average at prefrontal electrodes. Associations were specific to SWA, as measures of subjective sleepiness and alertness; objective alertness, circadian preference, neurocognitive status, fast spindle density during stage 2 did not correlate with episodic memory change.

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LEFT HIPPOCAMPAL ACTIVATION TO MEDIAL PREFRONTAL CORTEX ACTIVATION IN THE CONTEXT OF SUCCESSFUL MEMORY RETRIEVAL

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Conclusion These data alone do not establish causality. They do not prove that the disruption in NREM SWA directly causes impaired memory retention in older adults, as there may be unmeasured factors beyond the collection of co-factors that could account for the statistical associations between each of these variables. However, our findings make clear that these three a priori targets (mPFC brain atrophy, NREM SWA and delayed memory retention) are not independent of each other and that other potentially unaccounted for factors would themselves be associated with these specific sleep and atrophy changes in predicting memory.

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Схематическая модель Aging is associated with gray matter atrophy, which mediates the degree of SWA disruption, with SAW in turn mediating the degree of impaired memory retention.

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Sleep monitoring and EEG analysis PSG sleep monitoring on the experimental night was recorded using a Grass Technologies Comet XL system (Astro-Med), including 19-channel EEG placed using the standardized 10– 20 system, electrooculography recorded at the right and left outer canthi (right superior, left inferior), and electromyography. Reference electrodes were recorded at both the left and right mastoid (A1, A2). Data were digitized at 400 Hz, and stored unfiltered (recovered frequency range of 0.1–100 Hz), except for a 60-Hz notch filter. Sleep was scored using standard criteria{58}. Sleep monitoring on the screening night was recorded using a Grass Technologies AURA PSG Ambulatory system (Astro-Med), similar to as described above save for the following exceptions: EEG was recorded at nine derivations (F3, FZ, F4, C3, CZ, C4, P3, P4, OZ) and data were digitized at 200 Hz. During full PSG screening nights, nasal/oral airflow, abdominal and chest belts, and pulse oximetry were also monitored to screen for the presence of sleep apnea. EEG data from the experimental night were imported into EEGLAB and epoched into 5-s bins. Epochs containing artifacts were rejected, and the remaining epochs were filtered between 0.4 and 50 Hz. A fast Fourier transform was then applied to the filtered EEG signal at 5-s intervals with 50% overlap and employing Hanning windowing. Analyses in the current report focused, a priori, on SWA, defined as absolute and relative spectral power between 0.8–4.6 Hz during SWS. Spectral power during SWS was chosen because staging requires absolute amplitude above a standard threshold requiring, by definition, slow-wave detection. Relative spectral power was chosen because it accounts for individual differences in overall absolute spectral power potentially resulting from differences in brain to scalp distance, skull thickness, impedance, head size and the potential effects of different sleep recording systems, standardizing spectral power across subjects.

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